海角社区

海角社区 Computer Science Associate Professor Elias Bou-Harb recently received a $300,000 grant from the National Science Foundation (NSF) and a $126,000 grant from the Secret Service for his research in cybersecurity.

As part of a collaborative project with University of California San Diego, the NSF awarded Bou-Harb $300,000 to work on iVoyager, a transformative cyberinfrastructure designed to enable researchers to effectively explore the landscape of internet threats through scalable cyber threat intelligence gathering.

鈥渋Voyager facilitates the rapid development and scalable deployment of distributed, dual-stack reactive telescopes that support both IPv4 and IPv6 address spaces,鈥� Bou-Harb said. 鈥淲e鈥檙e operationalizing our reference design to collect longitudinal datasets that will enable the use of machine learning and artificial intelligence (AI) for cyber threat hunting, anomaly detection, and malware analysis.鈥�

Currently, researchers use network telescopes to capture incoming unsolicited traffic known as Internet Background Radiation, which has helped identify victims of denial-of-service attacks and reveal patterns of malicious Internet activities. However, the telescope approach is aging out because it only captures certain types of security events, and malicious actors have evolved their tactics specifically to evade detection. While researchers have supplemented telescopes with honeypots that react to unsolicited traffic to lure attackers into revealing their methods, both approaches face the critical challenge of the growing adoption of IPv6.

鈥淚t鈥檚 important to note that iVoyager won鈥檛 replace existing network telescopes or honeypots,鈥� Bou-Harb said. 鈥淚nstead, it complements these cyberinfrastructures by providing additional datasets for more comprehensive cyber threat analysis.鈥�

Bou-Harbs鈥檚 $126,000 grant comes from the Secret Service for his research in forensics. Security professionals currently face the challenge of identifying and tracking countless IoT devices deployed across diverse network environments. The ability to quickly and accurately fingerprint these devices has become critical to modern cybersecurity operations.

鈥淯nder my leadership, our team has successfully developed and deployed a comprehensive IoT fingerprinting system that addresses three fundamental scientific problems plaguing the field,鈥� Bou-Harb said. 鈥淥ur solution takes a multi-faceted approach to device identification by combining passive-based algorithms for non-intrusive monitoring with active-based techniques for targeted identification.鈥�

Bou-Harb鈥檚 system leverages network topology centric analysis while employing a sophisticated combination of machine learning and statistical approaches to ensure maximum accuracy. The entire architecture is both adaptable and scalable, capable of handling networks of any size.

鈥淭he impact for state, local, tribal and territorial partners cannot be overstated,鈥� Bou-Harb said. 鈥淲e鈥檝e created an automated and portable tool that can be deployed on any network without extensive setup or configuration. Every aspect has been designed with investigation readiness in mind, making it purpose-built for forensic and security applications.鈥�

海角社区 Division of Computer Science and Engineering Chair Ibrahim Baggili is proud to have Bou-Harb as part of his team.

鈥淓lias Bou-Harb keeps securing wins for 海角社区 proving that building teams that win is not just about funding, but about shaping innovation, training talent, and protecting our digital future,鈥� Baggili said.

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